Many compression algorithms are known. One such compression algorithm is the JPEG standard. The JPEG (Joint Photographic Experts Group) is the name of a committee and the name of the international standard adopted by that committee which applies to compression of graphic images (pictures). The JPEG standard is one of the most popular and comprehensive continuous tone, still frame compression standards. JPEG defines a lossy baseline coding system, which is based on the Discrete Cosine Transform (DCT).
Lossy image compression refers to a technique wherein the compressed data cannot be decompressed into an exact copy of the original image, i.e., there is a loss of quality of the final image. An important goal in lossy image compression is to achieve maximum compression while still obtaining high image quality of the decompressed image. Too great of a compression amount often introduces unacceptable artifacts into the decompressed image.
In the JPEG lossy baseline system, compression is performed by first dividing the image into non-overlapping blocks of size 8 by 8 pixels, which are processed in an order from left to right, top to bottom. After a normalization step, a two-dimensional DCT is applied to each block. This transform, similar to a Fourier transform, produces a transformed block (matrix) in the frequency domain. The first coefficient (location 0, 0) in the transformed block is a constant that represents the average or DC component of the 64 image elements (pixels) included in each image block. The remaining coefficients, which represent AC components of the 64 image elements, describe higher frequencies found in the block.
The DCT coefficients are then quantized using a defined quantization table and reordered using a zigzag pattern to form a one-dimensional sequence of quantized coefficients. Lossless entropy coding, such as Huffman coding, may then be applied to the resulting sequence to produce the compressed data.
Although there are a number of settings that may be predefined to achieve different compression ratios, one parameter, called the quality factor, may be adjusted in JPEG compression. The quality factor is a single number in an arbitrary, relative scale and is often adjusted on an image-by-image basis. A higher quality factor provides a relatively high quality decompressed image, but requires a relatively large file (less compression). A lower quality factor provides greater compression with a correspondingly smaller file size. There may be more visible defects or artifacts, however, in the decompressed image.
In many image processing application programs, such as image noise removal, image segmentation, etc., accurate knowledge of the noise level present in the image is of crucial importance for tuning the parameters of the corresponding algorithms. When applying a post processing algorithm, or after market software, to enhance the output images from digital cameras, the noise present in the images may significantly impact the effectiveness of the image processing. Precise information about the noise present in these images may be used, however, for improving the performance of these algorithms, by tuning the parameters of the algorithms to the noise level.
In today's digital images, the type and level of the noise generated by a digital camera depends on the series and brand of the camera, as well as the camera settings (ISO, shutter speed, aperture and flash on/off). The noise level also varies based on the pixel brightness level, as pixels exposed to more light generally have less noise. In addition, the noise level varies depending on the pixel location, as pixels located on a boundary are exposed to less light than pixels located in the central of the image area due to the limitation of an optical lens. The noise level, therefore, is not uniformly distributed in digital images, while most image processing algorithms assume a uniformly distributed noise level.
As will be explained, the present invention provides a system and method for estimating noise levels in JPEG images, so that after market software may improve performance of post processing of JPEG image data.